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Read More →For aspiring AI professionals in Kochi, Uncodemy offers a 5–6 month instructor-led live online RAG Engineering program. The curriculum explores document ingestion and chunking, embeddings, vector databases, retrieval pipelines, hybrid search, and production RAG deployment. Targeted at developers, data scientists/ML engineers, and aspiring AI engineers, it features 13 modules, 90+ live sessions, 140+ hours, and an enterprise RAG capstone. Fee: ₹17,500 + 18% GST = ₹20,650. EMI starting at ₹4,032/month.
Learn from 8+ years experienced professionals
Build real LLM test suites, not just theory
Get lifetime access to recorded sessions & materials
Resume Building, Mock Interviews & Job Support
Certificate of Completion from Uncodemy
Weekday & Weekend Online & Offline
Graduates of Uncodemy's LLM Engineering program leave with practical, applied skills in LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. After training and career preparation, eligible learners can pursue positions such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Ahmedabad learners get refreshed periodically — inspect verified outcomes at uncodemy.com/placement.
Placed at:Cognizant
LLM engineering is the specialised craft of architecting, assembling, refining and shipping applications that rely on large language models. Traditional software engineering depends on deterministic logic, while data science pivots around predictive modelling from data — LLM engineering, by contrast, contends with probabilistic model behaviour, prompt design, retrieval pipelines and model adaptation. It lies at the meeting point of software engineering, machine learning and product development, translating raw LLM capabilities into dependable, production-grade features.
What does an LLM engineer do? An LLM engineer engages extensively with LLM APIs and SDKs, assembles RAG pipelines powered by embeddings and vector databases, fine-tunes models for specific domains, constructs LLM agents capable of tool calling, inspects model outputs, and deploys LLM-driven applications. Their daily routine encompasses Python scripting, prompt engineering, retrieval evaluation, API integration, and leveraging frameworks like LangChain to unite models, data and tools into coherent applications.
The work of LLM Engineering revolves around building, fine-tuning, and deploying applications powered by LLMs. In contrast, Generative AI & Agentic AI highlights autonomous agents, while Data Science is focused on predictive modelling.
| Aspect | LLM Engineering | Generative AI | Data Science |
|---|---|---|---|
| Core focus | Building, fine-tuning & deploying LLM-powered applications | Building GenAI apps + autonomous AI agents/multi-agent systems | Predictive modelling from data |
| Coding depth | High | Moderate to High | High |
| Typical entry salary | ₹6–10 LPA (Entry-Level LLM Engineer) | [CONFIRM per GenAI course sheet] | ₹4–8 LPA (per Data Science course sheet) |
| Uncodemy program duration | 5–6 months | ~3–4 months (indicative) | 8–9 months |
Salary ranges are indicative and vary by role, skills, experience, location and employer.
This LLM Engineering course runs for 5–6 months in a completely live online format, with 100+ live sessions and over 160 hours of learning. It includes 13 modules that take you from Generative AI fundamentals to Python for LLM engineering, ML & NLP essentials, transformer architecture, prompt engineering, LLM APIs & SDKs, embeddings & vector databases, RAG, LLM application development, fine-tuning, LLM agents & tool calling, evaluation & deployment, and ends with a 20-hour Enterprise LLM capstone. Each module pairs theory with applied exercises using real tools, and the program concludes with hands-on projects, RAG applications, and an enterprise capstone. Delivery is 100% live online, serving learners in Ahmedabad and nationwide.
Who should join this course:
Eligibility: Programming fundamentals are helpful but not mandatory — Python is taught from Module 2 onward. Comfort with basic ML/NLP concepts is a plus but built up in Module 3. A laptop with stable internet is required for practical sessions.
Pick a batch slot that lines up with your schedule. Live online batches run on IST. You can book a free demo class for an initial preview, or enrol in an upcoming weekday or weekend live batch — designed for working professionals and students alike, with flexible timings and hands-on training.
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 16oct | 07:30 PM – 08:30 PM | Mr. Irshad | 01Seat |
| 22oct | 02:00 PM – 03:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| 26oct | 10:30 AM – 11:30 AM | Mr. Irshad | 01Seat |
| 30oct | 12:00 PM – 01:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 27oct | 03:00 PM – 05:00 PM | Mr. Irshad | 02Seats |
8+ new batches start every month. All timings are in IST. Seats are limited and updated daily.
The syllabus is organised into 13 modules covering 160 hours. The order follows how LLM engineering actually works: foundations → Python → ML/NLP basics → transformer architecture → prompt engineering → LLM APIs → embeddings/vector DBs → RAG → application development → fine-tuning → agents & tool calling → evaluation/deployment → capstone. Each module includes practical exercises with real tools, and the program closes with hands-on projects, RAG applications and an enterprise LLM capstone.
| # | Module | Hours | Tools |
|---|---|---|---|
| 1 | LLM & Generative AI Foundations | 8 | ChatGPT, Gemini, Claude |
| 2 | Python for LLM Engineering | 10 | Python, Git |
| 3 | Machine Learning & NLP Fundamentals | 10 | Python, scikit-learn, NLTK |
| 4 | Transformers & LLM Architecture | 12 | Hugging Face Transformers |
| 5 | Prompt Engineering & Structured Outputs | 8 | ChatGPT, Gemini, Claude |
| 6 | Working with LLM APIs & SDKs | 10 | OpenAI/Gemini/Claude APIs, Python |
| 7 | Embeddings & Vector Databases | 10 | FAISS, Chroma, Pinecone |
| 8 | Retrieval-Augmented Generation (RAG) | 15 | LangChain, Vector DBs |
| 9 | LLM Application Development | 12 | LangChain, Python |
| 10 | Fine-Tuning & Model Adaptation | 15 | Hugging Face, LoRA |
| 11 | LLM Agents & Tool Calling | 15 | LangChain, Python |
| 12 | LLM Evaluation, Optimization & Deployment | 15 | LangSmith, Docker, Python |
| 13 | Enterprise LLM Projects & Capstone | 20 | All tools |
| Total | 160 Hours | 15+ tools | |
Upon completing all 13 modules, the assignments and the Enterprise LLM capstone project, you will be granted the Uncodemy LLM Engineering Program Certificate. The certificate lists the program name, duration, tools covered and completion date. It stays verifiable online at certificate.uncodemy.com and acts as a formal record of your successful completion of the Uncodemy LLM Engineering program.
The certificate is based on the practical work you do during the program — including hands-on RAG applications, fine-tuning exercises and the 20-hour Enterprise LLM capstone project. Throughout the program, you will be working with LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, prompt engineering tools, fine-tuning frameworks and evaluation/observability tools.
This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor provider whose APIs are taught in this course. Certificate verification process pending confirmation.
Uncodemy Certificate Verification Online Certificate Verification & Download certificate.uncodemy.com_2.webp)
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LLM APIs & SDKs
LangChain
Vector Databases
Python
Hugging Face
Prompt Engineering
Fine-Tuning
Evaluation/Observability
Git & GitHub
Uncodemy is an IT training institute centred on career growth, operated by Uncodemy Edutech Pvt. Ltd. Boasting 14+ years of training excellence, classroom facilities in Delhi and Noida, and live online classes reaching students across India, Uncodemy provides instructor-led training for emerging technologies.
In this LLM Engineering program, learners develop RAG applications, fine-tune models, design LLM agents with tool calling, and complete an enterprise LLM capstone project. The training covers how LLM-powered applications are engineered in production — prompt design, retrieval pipelines, model adaptation and deployment. You can read the full module-by-module curriculum before you enrol.
In addition to training, Uncodemy delivers instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What that support includes — and what it does not — is set out in our career support policy, along with the eligibility conditions published before enrolment rather than after payment.
If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Madurai and Tamil Nadu learners.
Portfolio/capstone project review:Your hands-on RAG applications, fine-tuning work and enterprise LLM capstone are reviewed and refined into a portfolio an interview will find credible.
Resume & LinkedIn:We build your resume around LLM engineering keywords and measurable outcomes, and align your LinkedIn profile to match.
Interview preparation:System design for LLM applications, RAG pipeline debugging, fine-tuning trade-off questions and LLM engineering case studies specific to AI hiring.
Mock interviews:Sessions with industry trainers, followed by written feedback on what to fix.
Opportunity sharing:Relevant openings from our hiring network of 850+ companies are shared with you, with support through the application and interview process.
Continued support:This is active assistance, not a guarantee of employment — no training institute can honestly promise a job. Support continues after your program ends for learners who stay engaged with the process.
The people who actually teach this course
Uncodemy maintains a clear separation between two roles that many institutes combine. Trainers deliver the live sessions. Domain reviewers — independent specialists who don't teach the batch — confirm that the curriculum stays technically accurate and current. For this program, curriculum and technical content are reviewed by Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari. This ensures the person teaching a course is not the only person verifying whether its content is correct.
Every trainer and domain reviewer associated with Uncodemy is published by name, with their domain and background — you can look them up before you enrol rather than after.
Senior Data Science Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.
Data Analytics & AI Trainer
ExpertisePython · SQL · Machine Learning · Tableau · Artificial Intelligence · Deep Learning · Power BI · MLOps
8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.
Data Analytics & AI Trainer
ExpertiseExcel, SQL, Python, statistics, Power BI, Tableau and Generative AI
7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.
Data Analytics Trainer
ExpertisePython · SQL · Excel · Power BI · Tableau · ML · DL · NLP · Time Series · IoT Devices · Prompt Engineering · Chatbots
5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.
Data Analytics Trainer
ExpertiseAdvanced Excel · SQL · Power BI · Tableau · Python · Data Visualisation · Statistics
Trainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.
Data Analytics Trainer
Expertise
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Enrol in Uncodemy's LLM Engineering course tailored for Ahmedabad learners. Through live, instructor-led online sessions, you will cultivate practical command over LLM APIs, RAG pipelines, fine-tuning and LLM agents — reinforced by real projects and an enterprise LLM capstone. Kickstart your LLM engineering path with structured training and career preparation.
| Role | Core Tools |
|---|---|
| LLM Engineer | LLM APIs, LangChain, Python, Vector DBs |
| AI Engineer | Python, Hugging Face, RAG, Fine-Tuning |
| RAG/AI Application Engineer | LangChain, Vector DBs, Embeddings |
| Generative AI Engineer | LLM APIs, Prompt Engineering, Python |
| ML Engineer (LLM-focused) | Hugging Face, Fine-Tuning, Evaluation Tools |
| AI Solutions Architect (Junior) | LangChain, Deployment Tools, Python |
| Role | Salary Range |
|---|---|
| Entry-Level LLM Engineer | ₹6–10 LPA |
| LLM Engineer / AI Engineer | ₹10–18 LPA |
| Mid-Level LLM Engineer | ₹15–25 LPA |
| Generative AI Engineer | ₹10–20 LPA |
| RAG / AI Application Engineer | ₹10–20 LPA |
| Senior LLM Engineer | ₹20–35 LPA |
| Lead AI / LLM Engineer | ₹25–45 LPA |
| Factor | This Program |
|---|---|
| Duration | 5–6 months |
| Learning hours | 160+ |
| Live sessions | 100+ |
| Tools | 15+ |
| Fine-tuning module | Dedicated 15-hour module |
| Capstone | 20-hour Enterprise LLM project |
| Career support | Dedicated Career & Placement Assistance |
| If you want... | Recommend |
|---|---|
| Full LLM Engineering career transition | This program |
| Quick prompt-engineering upskilling only | Consider AI Testing or GenAI course |
| Already strong in traditional ML, want to specialise in LLMs | This program |
| Building AI agents specifically | Consider Generative AI & Agentic AI course |
The program stretches across 5–6 months and delivers 160+ hours of learning via 100+ live sessions. Weekday and weekend batch options are both available.
Prior experience is not required. Programming fundamentals help but aren't mandatory — Python is taught from Module 2 onward, and core ML/NLP topics are addressed in Module 3. A laptop with stable internet is needed.
You will work with 15+ tools including LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, prompt engineering tools, fine-tuning frameworks, evaluation/observability tools, and Git & GitHub.
Yes, both are covered in detail. Module 10 handles Fine-Tuning & Model Adaptation (15 hours) and Module 11 handles LLM Agents & Tool Calling (15 hours). Both include hands-on work.
The capstone is Module 13: Enterprise LLM Projects & Capstone (20 hours). You will build a complete end-to-end LLM-powered application combining RAG, fine-tuning, agents and deployment.
All 100+ sessions are instructor-led and live. Recordings are provided afterwards so learners can revise any topic at their own pace.
The program fee is ₹17,500 + 18% GST, taking the total to ₹20,650. The same fee applies across every city and delivery format.
EMI starts at ₹4,032 per month. The exact amount, tenure and eligibility depend on the payment or financing option selected. A counsellor can confirm the specifics.
Yes. A demo session is available where you can observe the teaching approach, meet the trainer and review the curriculum before deciding. Contact us to reserve a slot.
Yes — Dedicated Career & Placement Assistance covers resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing through our 850+ company hiring network. However, we do not guarantee employment.
Entry-level LLM Engineer roles typically offer around ₹6–10 LPA (indicative). Actual results vary by skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.
Indicative market ranges: Entry-Level ₹6–10 LPA, Mid-Level ₹15–25 LPA, Senior ₹20–35 LPA and Lead ₹25–45 LPA. Actual offers depend on role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary.
Typical roles include LLM Engineer, AI Engineer, RAG/AI Application Engineer, Generative AI Engineer, ML Engineer (LLM-focused) and AI Solutions Architect (Junior).
The course fits developers wanting to specialise in LLM-powered applications, data scientists and ML engineers upskilling into LLM engineering, aspiring AI engineers, and working professionals transitioning into GenAI/LLM roles.
All data is drawn from Uncodemy's internal records and publicly available review platforms. Placement and salary outcomes vary by learner, skills, experience, location, employer and market conditions. Career and placement assistance is not a guarantee of employment or a specific salary package.
This LLM Engineering course is delivered fully live online across India, including for Ahmedabad learners. Classroom training for other courses is available at our Delhi and Noida centres. Ahmedabad learners typically attend live online.
No — it is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor whose APIs are taught in this course.
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